Li-Ching Wu

Li-Ching Wu

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

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Previous Organizations / Institutes

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Li-Ching Wu has a total of 43 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Suboptimal Plasma Vitamin C Is Associated with Lower Bone Mineral Density in Young and Early Middle-Aged Men: A Retrospective Cross-Sectional Study

    by Kuo-Mao Lan, Li-Kai Wang, Yao-Tsung Lin, Kuo-Chuan Hung, Li-Ching Wu, Chung-Han Ho, Chia-Yu Chang, Jen-Yin Chen

    Background: This study was conducted to evaluate associations between bone mineral density (BMD) and four selected circulating nutrients, particularly vitamin C, among adults aged 20–49 years. Methods: In this retrospective cross-sectional study, the lumbar spine BMD of 866 men and 589 women were measured by dual-energy X-ray absorptiometry and divided into tertiles, respectively. Logistic regressions were used to identify the predictors of low BMD by comparing subjects with the highest BMD to those with the lowest. Results: Multivariate logistic regressions identified suboptimal plasma vitamin C (adjusted odds ratio (AOR) 1.64, 95% confidence interval (CI) 1.16, 2.31), suboptimal serum vitamin B12 (AOR 2.05, 95% CI 1.02, 4.12), and low BMI (BMI < 23) (AOR 1.68, 95% CI 1.12, 2.53) as independent predictors for low BMD in men. In women, low BMI was the only independent predictor for low BMD. Plasma vitamin C, categorized as suboptimal (≤8.8 mg/L) and sufficient (>8.8 mg/L), was positively significantly correlated with the lumbar spine BMD in men, but there was no association in women. Conclusions: Plasma vitamin C, categorized as suboptimal and sufficient, was positively associated with the lumbar spine BMD in young and early middle-aged men. A well-designed cohort study is needed to confirm the findings.


  • Open Access

    Discrimination of Methicillin-resistant Staphylococcus aureus by MALDI-TOF Mass Spectrometry with Machine Learning Techniques in Patients with Staphylococcus aureus Bacteremia

    by Po-Hsin Kong, Cheng-Hsiung Chiang, Ting-Chia Lin, Shu-Chen Kuo, Chien-Feng Li, Chao A. Hsiung, Yow-Ling Shiue, Hung-Yi Chiou, Li-Ching Wu, Hsiao-Hui Tsou

    Early administration of proper antibiotics is considered to improve the clinical outcomes of Staphylococcus aureus bacteremia (SAB), but routine clinical antimicrobial susceptibility testing takes an additional 24 h after species identification. Recent studies elucidated matrix-assisted laser desorption/ionization time-of-flight mass spectra to discriminate methicillin-resistant strains (MRSA) or even incorporated with machine learning (ML) techniques. However, no universally applicable mass peaks were revealed, which means that the discrimination model might need to be established or calibrated by local strains’ data. Here, a clinically feasible workflow was provided. We collected mass spectra from SAB patients over an 8-month duration and preprocessed by binning with reference peaks. Machine learning models were trained and tested by samples independently of the first six months and the following two months, respectively. The ML models were optimized by genetic algorithm (GA). The accuracy, sensitivity, specificity, and AUC of the independent testing of the best model, i.e., SVM, under the optimal parameters were 87%, 75%, 95%, and 87%, respectively. In summary, almost all resistant results were truly resistant, implying that physicians might escalate antibiotics for MRSA 24 h earlier. This report presents an attainable method for clinical laboratories to build an MRSA model and boost the performance using their local data.


  • Open Access

    Prevalence and Predictors of Insufficient Plasma Vitamin C in a Subtropical Region and Its Associations with Risk Factors of Cardiovascular Diseases: A Retrospective Cross-Sectional Study

    by Yao-Tsung Lin, Li-Kai Wang, Kuo-Chuan Hung, Chia-Yu Chang, Li-Ching Wu, Chung-Han Ho, Jen-Yin Chen

    Background: to evaluate the prevalence and predictors of insufficient plasma vitamin C among adults in a subtropical region and its associations with cardiovascular disease risk factors including dyslipidemia and lipid-independent markers, namely homocysteine, high-sensitivity C-reactive protein (hs-CRP) and lipoprotein(a). Methods: Data of this retrospective cross-sectional study were extracted from electronic medical database of a Medical Center. Based on plasma vitamin C status, subjects were split into two groups—subjects with sufficient and insufficient plasma vitamin C levels (p < 0.001). There were no differences in total cholesterol, low-density lipoprotein cholesterol and lipoprotein(a) between groups. Conclusions: There was a high prevalence of insufficient plasma vitamin C in the subtropical region, which indicates that insufficient plasma vitamin C remains a public health issue. Further study is needed to confirm these findings and to determine the underlying mechanisms.


  • Open Access

    Shortening the Time of the Identification and Antimicrobial Susceptibility Testing on Positive Blood Cultures with MALDI-TOF MS

    by Ya-Wen Tsai, Ting-Chia Lin, Hsiu-Yin Chou, Huei-Ya Hung, Che-Kim Tan, Li-Ching Wu, I-Jung Feng, Yow-Ling Shiue

    The current processes used in clinical microbiology laboratories take ~24 h for incubation to identify the bacteria after the blood culture has been confirmed as positive and fa further ~24 h to report the results of antimicrobial susceptibility tests (ASTs). Patients with suspected bloodstream infection are treated with empiric broad-spectrum antibiotics but delayed targeted antimicrobial therapy. This study aimed to develop a method with a significantly shortened turnaround time for clinical application by identifying the optimal incubation period of a subculture. A total of 188 positive blood culture samples obtained from Nov. 2019 to Aug. 2020 were included. Compared to the conventional 24-h incubation for bacterial identification, our approach achieved 96.1% and 97.4% identification accuracy after shortening the incubation time to 4.5 and 3.5 h for gram-positive (GP) and gram-negative (GN) bacterial samples, respectively. Samples from short-term incubation without any intermediate step or process were directly subjected to analysis with the Phoenix M50 AST. Compared to the conventional disk diffusion AST, the category agreements for GP (excluding Streptococcus spp.), Streptococcus spp., and GN bacterial samples were 91.8%, 97.5%, and 92.7%, respectively. Our approach significantly reduced the average turnaround time from 48 h to 28 h for reporting bacterial identity and decreased average AST from 72 h to 50.3 h compared to the conventional methods. Accordingly, this approach allows a physician to prescribe the appropriate antibiotic(s) ~21.7 h earlier, thereby improving patient outcomes.


  • Open Access

    Prognostic Significance of ROR2 Expression in Patients with Urothelial Carcinoma

    by Cheng-Fa Yeh, Ti-Chun Chan, Hung-Lung Ke, Tzu-Ju Chen, Li-Ching Wu, Hsiang-Ying Lee, Yu-Ching Wei, Wen-Jeng Wu, Chien-Feng Li, Wei-Ming Li

    We investigated the association of receptor tyrosine kinase-like orphan receptor 2 (ROR2) expression with clinicopathological features and oncologic outcomes in large urothelial carcinoma (UC) of the upper tract (UTUC) and urinary bladder (UBUC) cohorts. Through transcriptomic profiling of a published dataset (GSE31684), ROR2 was discovered to be the most upregulated gene during UC progression, focusing on the JNK cascade (GO:0007254). Initially, the evaluation of ROR2 mRNA expression in 50 frozen UBUCs showed significantly upregulated levels in high-stage UC. Moreover, high ROR2 immunoexpression significantly correlated with high tumor stage, high tumor grade, lymph node metastasis, and vascular invasion (all p < 0.05). In multivariate analysis, after adjusting for standard clinicopathological features, ROR2 expression status was an independent prognosticator of cancer-specific survival and metastasis-free survival in UTUC and UBUC (all p < 0.01). In the subgroup analysis, it also significantly predicted bladder tumor recurrence in non-muscle invasive UBUC. Furthermore, the GO enrichment analysis showed that fatty acid, monocarboxylic acid, carboxylic acid metabolic processes, negative regulation of neutrophil migration, and negative regulation of granulocyte and neutrophil chemotaxis were significantly enriched by ROR2 dysregulation. In conclusion, high ROR2 immunoexpression was associated with aggressive pathological characteristics in UC and independently predicted worse prognosis, suggesting it could play roles in clinical risk stratification and therapy decisions.


  • Open Access

    Hepatitis C Virus Subtypes Novel 6g-Related Subtype and 6w Could Be Indigenous in Southern Taiwan with Characteristic Geographic Distribution

    by Hung-Da Tung, Pei-Lun Lee, Jyh-Jou Chen, Hsing-Tao Kuo, Ming-Jen Sheu, Chun-Ta Cheng, Tang-Wei Chuang, Hsu-Ju Kao, Yu-Hsun Wu, Mai-Gio Pang, et al.

    Hepatitis C virus (HCV) genotype (GT) 6 is the most genetically diverse GT and mainly distributed in Southeast Asia and south China but not Taiwan. Earlier studies showed the major HCV GTs in Taiwan were GT 1b and 2 with very rare GT 6 except in injection drug users (IDUs), and subtype 6a is the main GT 6 subtype among IDUs. Recently, we reported a much higher prevalence (18.3%) of GT 6 in Tainan City, southern Taiwan. This study was designed to clarify the subtypes of GT 6 in this endemic area. A total of 3022 (1343 men and 1679 women) HCV viremic patients were enrolled. Subtypes of GT 6 were determined by sequencing of core/E1 and nonstructural protein 5B in 322 of 518 GT 6 patients. The overall GT 6 prevalence rate was 17.1% (518/3022), with higher prevalence districts (>25%) located in northern Tainan. A novel 6g-related subtype is the most prevalent subtype (81.0%), followed by 6w (10.8%), 6a (7.5%), and 6n (0.7%). The high GT 6 prevalence in Tainan was mainly due to a novel 6g-related subtype and 6w. These two subtypes could be indigenous in Tainan with characteristic geographic distribution.